Framework for Audit Oversight INTERNATIONAL WORKSHOP ON ACCOUNTABILITY IN SCIENCE AND RESEARCH FUNDING JUNE 2 4, 2011

Transcription

1 Framework for Audit Oversight 1 INTERNATIONAL WORKSHOP ON ACCOUNTABILITY IN SCIENCE AND RESEARCH FUNDING JUNE 2 4, 2011

2 Overview 2 Forensic Audit and Oversight Forensic Techniques Identify Anomalies Framework for Grants Oversight Forensic Auditing Results

3 Federal Grants FY 09 Total: $753 Billion 3 $29,999,563 $14,580,480 $168,416,911 $540,035,693 Block Formula Project Cooperative Agreements Source: U.S Census, Federal Assistance Award Data System, FY 09 Q1-4

4 Grants Differ From Contracts GRANTS Intellectual Services for Public Good 4 CONTRACTS Specified Deliverables (Goods and Services) Award Budget Drawdowns Aggregate costs Salary percentages Contract Price Invoices Unit costs Salary hourly rates

5 Data Versus Information 5 An Endless Maze of Data... but No Information

6 Forensic Audit and Automated Oversight Definition of Forensic Audit Audit that looks for financial misconduct, abuse or wasteful activity More than Computer Assisted Audit Techniques (CAATs) Creates Relationships, Checks Calculations, Performs Comparisons Assess limitless number of analytical relationships Summarize large volume of data Database comparison 6

7 Forensic Audit Techniques: Benefits 100% Review Versus Statistical Sampling Tests not Limited to Predetermined Data Formats and/or Relationships Automated Oversight Continuous monitoring Quick response Confirm Audit Findings Have Been Corrected Identify Anomalies to Review, Save Audit Time and Costs 7

8 What is Data Mining? 8 The Use of Machine Learning and Statistical Analysis to Find Patterns in Data Sets Use Structured Query Language (SQL): If You Know Exactly What You What to Find Use Data Mining: When You Know Vaguely What You Are Looking for Data Mining May Confirm Audit Finding Was Corrected

9 Forensic Techniques: Hardware and Software Applications Hardware SQL servers Mainframe (QMF) Docking stations Terminal server Software Data mining and predictive analytics, e.g., Clementine Data interrogation e.g., ACL, IDEA, MS Access, Excel Statistical analysis e.g., SPSS and SAS Link analysis I2 Lexis-Nexis Data conversion utilities (Monarch) Internet, open-source research Access to system query tools *NSF OIG does not endorse any commercial software 9

10 Common Data Analysis Tests and Techniques Join Summarization Corrupt data (conversion) Blank fields (noteworthy if field is mandatory) Invalid dates Bounds testing Completeness Uniqueness Invalid codes Unreliable computed fields Illogical field relationships Trend analysis Duplicates 10 *NSF OIG does not endorse any commercial software

11 Growing a Forensic Audit Capability Audit programs should include data analysis steps Develop Organizational Capability All audit staff should have basic skill with ACL, IDEA, Access Forensic audit units perform more sophisticated analyses Targeted Audits are more efficient in time and cost Phased Development Hardware and software Staff: system savvy, analytical, business process knowledge Training, then immediate application to work 11 *NSF OIG does not endorse any commercial software

12 ACL Test to Identify Grant Charges Near or Subsequent to the Grant Expiration Date 12 *NSF OIG does not endorse any commercial software

13 Focus on Anomalies/Outliers 13 Anomalous Activity Normal Activity Anomalous Activity

14 Data Analysis: Database Comparisons 14 Awardee not yet Paid Awardee Paid and in Awardee Table Awardee Paid but not included in Awardee Table Awardee Table Disbursing Transactions

15 Focus on Anomalies/ Cash Draw Pattern 15 High Amount Drawn Low Amount Drawn High Amount Drawn

16 Cost Transfers Subsequent to Grant Expiration Date TRANSFERRED FROM: NSF GRANT ID 16 GRANT EXPIRATION DATE LEDGER POST DATE TRANSFERRED TO: NSF GRANT ID FINANICAL FINANCIAL OBJECT DESCRIPTION AMOUNT AMOUNT XXXXX80 SERVICES - DEPARTMENT RECHARGE 04/30/ /30/2009 (8,259.67) XXXXX60 8, XXXXX80 SUPPLIES & MATERIALS - OTHER 04/30/ /30/2009 (3,240.26) XXXXX60 3, XXXXX80 SERVICES - DEPARTMENT RECHARGE 04/30/ /30/2009 (777.31) XXXXX XXXXX80 SERVICES - DEPARTMENT RECHARGE 04/30/ /30/2009 (677.27) XXXXX XXXXX80 SERVICES - DEPARTMENT RECHARGE 04/30/ /30/2009 (545.00) XXXXX XXXXX80 LAB INSTRUMENTS & SUPPLIES 04/30/ /30/2009 (530.60) XXXXX XXXXX80 SERVICES - DEPARTMENT RECHARGE 04/30/ /30/2009 (528.86) XXXXX XXXXX80 SERVICES - DEPARTMENT RECHARGE 04/30/ /30/2009 (312.97) XXXXX XXXXX80 LAB INSTRUMENTS & SUPPLIES 04/30/ /30/2009 (274.36) XXXXX XXXXX80 LAB INSTRUMENTS & SUPPLIES 04/30/ /30/2009 (202.81) XXXXX XXXXX80 LAB INSTRUMENTS & SUPPLIES 04/30/ /30/2009 (197.17) XXXXX XXXXX80 SERVICES - DEPARTMENT RECHARGE 04/30/ /30/2009 (180.00) XXXXX XXXXX80 SERVICES - DEPARTMENT RECHARGE 04/30/ /30/2009 (164.42) XXXXX XXXXX80 LAB INSTRUMENTS & SUPPLIES 04/30/ /30/2009 (159.94) XXXXX XXXXX80 SERVICES - DEPARTMENT RECHARGE 04/30/ /30/2009 (80.00) XXXXX XXXXX80 SERVICES - DEPARTMENT RECHARGE 04/30/ /30/2009 (40.00) XXXXX XXXXX80 SUPPLIES & MATERIALS - OTHER 04/30/ /30/2009 (30.07) XXXXX XXXXX80 PERMITS-TAXES-FEES 04/30/ /30/2009 (9.50) XXXXX XXXXX80 OVERHEAD 04/30/ /30/2009 (7,618.80) XXXXX60 8, TOTAL (23,829.01) 24, *NSF OIG does not endorse any commercial software

17 Equipment Charges Incurred Immediately Before Grant Expiration Date 17 GRANT ID OBJECT DESCRIPTION GRANT EXPIRATION DATE TRANSACTION DATE LEDGER POST DATE FINANCIAL AMOUNT XXXXX42 CONSTRUCTION AND ACQUISITION 09/30/ /30/ /06/ , GRANT ID OBJECT DESCRIPTION GRANT EXPIRATION DATE TRANSACTION DATE LEDGER POST DATE FINANCIAL AMOUNT XXXXX27 INVENTORIAL EQUIPMENT 07/31/ /04/ /11/ , GRANT ID OBJECT DESCRIPTION GRANT EXPIRATION DATE TRANSACTION DATE LEDGER POST DATE FINANCIAL AMOUNT XXXXX77 INVENTORIAL EQUIPMENT 08/31/ /16/ /10/ , TOTAL 106, *NSF OIG does not endorse any commercial software

18 Payroll Charges Incurred Subsequent to the Grant Expiration Date 18 GRANT ID OBJECT DESCRIPTION GRANT EXPIRATION DATE TRANSACTION DATE LEDGER POST DATE FINANCIAL AMOUNT XXXXX31 WAGES - ACADEMIC 06/30/ /31/ /11/ , XXXXX31 OVERHEAD-CONTRACT&GRANT 06/30/ /31/ /11/2008 8, XXXXX31 TUITION-FULL FEE REMISSION-RA 06/30/ /31/ /11/2008 4, XXXXX31 GRAD STUDENT HEALTH INSURANCE 06/30/ /31/ /11/2008 1, XXXXX31 LEAVE ACCRUAL 06/30/ /31/ /11/ XXXXX31 SOCIAL SECURITY REGENTS CONTR 06/30/ /31/ /11/ XXXXX31 OE-EMPLOYER UC OPEB CONTRIB-UC 06/30/ /31/ /11/ XXXXX31 WORKER COMPENSATION INSURANCE 06/30/ /31/ /11/ XXXXX31 MEDICARE 06/30/ /31/ /11/ XXXXX31 EMPLOYEE SUPPORT PROGRAM 06/30/ /31/ /11/ XXXXX31 UNEMPLOYMENT INSURANCE 06/30/ /31/ /11/ XXXXX31 GRAD STUDENT PARTIAL FEE REM 06/30/ /31/ /11/ XXXXX31 NON-INDUSTRIAL DISABILITY CONT 06/30/ /31/ /11/ XXXXX31 OE-BENEFITS ADMIN ASSESSMENT 06/30/ /31/ /11/ XXXXX31 SPECIAL LIFE INS CONTRIBUTION 06/30/ /31/ /11/ XXXXX31 REGENTS HEALTH INS CONTR 06/30/ /31/ /11/2008 TOTAL (14.72) 31, *NSF OIG does not endorse any commercial software

19 Forensic Audit Framework Finding Grant Fraud Risk 19 Set Objectives and Define Universe Map out End-to-End Process Identify systems, key processes and controls Obtain Transaction-Level Data Build Targeted Business Rules and Run Against Data PI/Institution patterns over time Risk factors Examine Anomalies

20 End to End Process for Grant Oversight 20 PRE-AWARD RISKS Funding Over Time Conflict of Interest False Statements False Certifications Duplicate Funding Inflated Budgets Candidate Suspended/Debarred ACTIVE AWARD RISKS Unallowable, Unallocable, Unreasonable Costs Inadequate Documentation General Ledger Differs from Draw Amount Burn Rate No /Late/Inadequate Reports Sub-awards, Consultants, Contracts Duplicate Payments Excess Cash on Hand/Cost transfers Unreported Program Income AWARD END RISKS No /Late Final Reports Cost Transfers Spend-out Financial Adjustments Unmet Cost Share

21 21 Look at Red Flag Areas Use Data Analysis to Identify Anomalies Breaks in Trends and Outliers are Potential Fraud Indicators The more red flags, the higher the risk. Award Notification HR System Recipient Project System Pay System The less red flags, the lower the risk. External Grants Portal Reports Acctg System Pre-Award Review Proposal System Internal Grants Portal Acctg System Post Award Monitoring Awards System Award Close-Out

22 Transaction Level Fraud Indicators: Grantee Data Cost Transfers to Other Projects or Contracts 22 Multiple Payments of Same Invoice Excessive Costs/Large Budget Reallocations Multiple Adjusting Entries, Spendout at End of Grant Unallowable Charges, Charges after Expiration

23 Payroll Fraud Indicators: Grantee Data 23 Payments after Grant Expiration Multiple Labor Categories for Same Employee Timesheets with Signature Differences Employee Background, Experience, or Education Does Not Meet Requirements Fictitious Employees, Such as Contractor s Relatives

24 Forensic Audit Results $1.5 Billion Dollars (US) Recovered Over 20 Years 24 Fraud Results (examples) $177M (US) Pell Grants (College loans) $ 30M (US) Student Loan Forgiveness $122M (US) Purchase Card Fraud (one agency) 100 Prosecutions 250 Disciplinary Actions

25 NSF Case Study: School District Trust is Not a Control Grantee Draws $2.1 Million in 3 Months Usual drawdown pattern: $250,000 quarterly Awardee cannot provide documentation 25 Total NSF Funds Awarded: $23.1 Million Audit Universe 2008: $13.1 Million OIG Questioned Costs: $ 4.2 Million NSF sustained: $ 3.3 Million

26 Future of Cost Records 26 Electronic Invoices and Receipts Debit Cards Funding Agency Can Access Transaction Charges Continuous Monitoring Grantee Performs Agency Performs

27 Additional Information 27 Questions? Dr. Brett M. Baker, CPA, CISA Assistant IG for Audit, NSF